Entropy driven cooperativity effect in multi-site drug optimization targeting SARS-CoV-2 papain-like protease

Abstract

Papain-like protease (PLpro), a non-structural protein encoded by SARS-CoV-2, is an important therapeutic target. Regions 1 and 5 of an existing drug, GRL0617, can be optimized to produce cooperativity with PLpro binding, resulting in stronger binding affinity. This work investigated the origin of the cooperativity using molecular dynamics simulations combined with the interaction entropy (IE) method. The regions' improvement exhibits cooperativity by calculating the binding free energies between the complex of PLpro-inhibitor. The thermodynamic integration method further verified the cooperativity generated in the drug improvement. To further determine the specific source of cooperativity, enthalpy and entropy in the complexes were calculated using molecular mechanics/generalized Born surface area and IE. The results show that the entropic change is an important contributor to the cooperativity. Our study also identified residues P248, Q269, and T301 that play a significant role in cooperativity. The optimization of the inhibitor stabilizes these residues and minimizes the entropic loss, and the cooperativity observed in the binding free energy can be attributed to the change in the entropic contribution of these residues. Based on our research, the application of cooperativity can facilitate drug optimization, and provide theoretical ideas for drug development that leverage cooperativity by reducing the contribution of entropy through multi-locus binding.

Keywords: Binding free energy; Cooperativity; Entropy contribution; Papain-like protease; Regional improvement of inhibitor.

Fig. 1

A The process of viral invasion into host cells and targeting of PLpro drugs improved in regions 1 and 5 (R1 and R5). B Improvements in R1 and R5 of drug GRL0617, with the improvements indicated in orange. The six drugs were divided into group 1 and group 2 according to the R5 improvement

Fig. 2

The energy contribution of each inhibitor region was calculated using the TI method or MM/GBSA + IE

Fig. 3

Comparison of various binding free energies of different regionally improved drugs with GRL0617. A ZN-2–184 (R1) and GRL0617, B XR8-106 (R5) and GRL0617, C XR8-89 (R1 and R5) and GRL0617, D XR1 (R5) and GRL0617, E XR8-24 (R1 and R5) and GRL0617. F Differences in enthalpy, entropy, and binding free energy term of the improved inhibitors and GRL0617

Fig. 4

A Stable hydrogen bonds (occupancy ≥ 70%) of each complex, marked with green dashed lines. B N deflection angle of each complex. C Residue energies for the first inhibitor improvement system. D Residue energies for the second inhibitor improvement system. E Differences between the improved inhibitors and GRL0617 in the enthalpy and entropy terms in P248. F Differences between the improved inhibitors and GRL0617 in the enthalpy and entropy terms in Q269

Fig. 5

A The distance between R166 and Y268. B 2D and 3D representations of dihedral angles in Y268 and Q269. C Dihedral angle for Y268, yellow indicates the deflection angle of C_α, and orange indicates the deflection angle of C_β. D Dihedral angle for Q269, yellow indicates the deflection angle of C_α, and orange indicates the deflection angle of C_β

Fig. 6

PC analysis of different inhibitors binding to PLpro and comparison of the conformations after binding. Blue represents the structure of PLpro after GRL0617 binding, green represents the structure of PLpro after inhibitor binding for A GRL0617-PLpro, B ZN-2–184-PLpro, C XR8-106-PLpro, D XR8-89-PLpro, E XR1-PLpro, F XR8-24-PLpro